Several people have expressed an interest in how the stories collected by The Harkive Project are analysed, so this post is a quick overview of some of the methods I’ve used. The post is accompanied by a sample data set, some code, and the walkthrough video above. If you would like to perform some analysis of your own you should be able to replicate the work shown here by adapting the script I’ve provided to your own datasets. However, if you are just interested in what happens to the data that the project gathers, I hope this post will still be useful and interesting.

The central methodological challenge of my research has been to devise a way of making sense of the large collection of texts Harkive has gathered since 2013. Because of my specific interest in the role that digital and data technologies play in the ways in which we experience music, one of the routes I’ve explored is computational processing. Broadly speaking, these are methods associated with what Gary Hall has called the ‘computational turn’ in humanities research, which he describes as “the process whereby techniques and methodologies drawn from computer science and related fields..are used to create new ways of approaching and understanding texts in the humanities”. You may have come across terms such as Digital Humanities, or Cultural Analytics – these are ways of describing the kind of academic work that Hall is talking about. From a media and cultural studies perspective, which is where I am located within BCMCR, digital and data technologies are of great interest because of their relationship to the ways in which cultural goods – which of includes popular music – are produced, distributed and consumed. Ultimately this means that they are very much a part of the cultures that are associated with those goods, and as such and understanding of those cultures means (in part) getting to grips with these technologies.

One way to think about approaching this is an observation from David Berry (2011), who points out that in order ‘to mediate an object, a digital or computational device requires that this object be translated into the digital code that it can understand’. I’m interested in what happens during that process of translation, and through practice-based research (and the Harkive project) I’m attempting to engage with the processes involved when real world experiences are abstracted into data points and analysis, and how this in turn plays a role in real world experiences.

We can think here, for instance, of algorithmic recommendation services and the ways in which we use them, and how these in turn influence (or not) the music we hear. To greater or lesser extents we each have an everyday relationship with data technologies, yet we don’t fully understand them, how they work, or what the potential consequences may be of our use of them. The aim of my research is to begin building an understanding of the relationship between computational technologies and our experiences of popular music, and in the specific terms of Harkive this becomes a question of what happens when a person experiencing music uses an online interface to describe that experience, which in turn creates a set of data points that can be processed, and ultimately used to help ‘produce’ a form of knowledge in terms of research findings. Clearly there are a huge number of steps involved here (abstractions, reductions, assumptions, and so on), each of which raise questions about both how we use digital technologies in our everyday lives, and also how we as researchers may approach this. What follows, then, is a very quick overview of how the descriptions of real world experiences collected by the Harkive project get processed, and how from a single line of text – a tweet – a large number of numeric and categorical abstractions can be created.

The data

For the purposes of this overview I have created a sample data set of 50 tweets gathered on 25th July 2017. This is a comparatively small data set, so the analysis presented below is not intended to demonstrate any solid findings. Rather, the data is being used here to illustrate a small number of computational processes.

The original data set contains 4 variables: unique numbers for both the stories and the users, the text of each tweet, and the time each tweet was sent. The process below will take those four variables as a starting point and create around 30 new variables that can be used in terms of exploring and visualising the stories.

Creating and visualising additional variables

In order to demonstrate what I mean by additional variables, the first part of the R script performs some simple calculations and data tidying. By counting the number of characters and words in each tweet, the following visualisations are produced. Here we can see some differences between the 50 tweets in terms of the amount of words and characters within each.

NB: 3 tweets appear to be over the 140-character limit for Twitter. As shown in the video, this is because they are either replies to multiple accounts, or else contain images.

Creating and exploring Document Term Matrix

The first stage of the analysis proper is to prepare the text within the tweets for processing. This includes the following steps:

Removal of all punctuation and other extraneous characters (e.g. @, #,//)

Removal of words that occur with very high frequency in written text, commonly known as ‘stopwords’. (e.g. the, it, at, were)

All text is converted to lower case (i.e. to avoid the counting of ‘Vinyl’ and ‘vinyl’ as separate entities)

Removal of ‘whitespace’, such as that which occurs between paragraphs

All words are ‘stemmed’ to their roots (i.e. to avoid ‘played’, ‘play’, ‘player’ and other derivations being counted a separate entries)

Removal of specific additional stopwords that occurred with very high frequency in this particular dataset – for example: ‘harkive’, ‘music’

Following that, a document term matrix is created. This represents each word within the corpus along on axis, and each document within the corpus along the other. The amount of times each unique word within the corpus appears in each document is contained within each cell. This enables the words within the matrix to be counted and visualised. If certain words appear at this point that are not required, or which may skew analysis, they can be removed. We can do this by adding them to the list of stopwords and then repeating the process of creating the document term matrix. Here we can see that the following words appear frequently within the dataset.

Topic modelling

David Blei defines Topic Modelling as a process that ‘provides a suite of algorithms to discover hidden thematic structure in large collections of texts. The results of topic modeling algorithms can be used to summarize, visualize, explore, and theorize about a corpus’. Topics can be understood as recurring data points (in this case, words) across a dataset (a corpus of text documents). The model, meanwhile, represents the extent to which each individual entry in a dataset (the Tweets) contains data points (topics/words). For a more detailed overview of using Topic Modelling, see Kailash Await’s excellent post from which my own script is derived, or read David Blei’s overview of the process

Because the data set in this particular instance is small the results will not be too instructive, but based on setting the process to organise the documents according to 3 topics we get the following results. Here are the top 5 words associated with each topic.

TOPIC 1: bbcmusic; nowplaying; spotify; perfect; piano

TOPIC 2: radio; begin; home; play; alarm

TOPIC 3: bus; morning; listen; start; ace

In terms of how this looks across the whole dataset, we can see that there is a fairly even split between topics. This process has also produced several new numeric and categorical variables that can be used at a later stage.

A closer look at the numbers involved here, however, reveal that the differences between documents, and thus their alignment with discrete topics, are more subtle than the overview suggests. Topic modelling is process that assumes documents within a corpus exhibit similarities to all topics in varying degrees. The differences between documents and their relationships to topics are often marginal and suggest that further enquiry is necessary before drawing conclusions based on topic allocation. Nevertheless, the process is a useful step in helping to think about the themes within a large collection of documents, particularly as it helps reveal associations between groups of words that may not necessarily be apparent through a manual reading of texts.

Sentiment analysis

Sentiment Analysis has been described by Bing Liu as the ‘computational study of opinions, sentiments and emotions expressed in text’. This process searches documents for the appearance of certain words that are individually scored, producing an overall value that marks a document as either exhibiting a positive, negative or neutral sentiment. This produces numeric scores based on text that enables individual documents to be grouped together according to numeric similarities, differences and statistical relationships. This part of the analysis is based on Julia Silge’s work on her own tweets. For further reading and a more critical view I would also suggest Annie Swafford‘s work.

In the case of the 50 tweets under examination here, the following visualisation is produced. As discussed in the video, we can see that three tweets have been marked as containing anger. This highlights certain limitations discussed by Annie Swafford in terms of the sentiment analysis libraries’ ability to deal with nuanced issues such as sarcasm and the use of certain words in difference contexts. In the case of one of the tweets designated as ‘angry’, the respondent named a song by DJ Shadow called ‘Horror Show’ – it would seem that the word ‘horror’ is responsible for the angry rating, when in actual fact the tweet (to my reading, at least) was anything but. As with Topic Modelling, the results of Sentiment Analysis need to be considered alongside a closer, manual engagement with the texts.

As with Topic Modelling above, Sentiment Analysis also produces several new variables. We can now use these along the other additional variables to produce some further visualisations

Combining variables

The additional variables created by both the Topic Modelling and Sentiment Analysis processes, along with the variables related to character counts and time, can be used in combination to explore the corpus a little further. For example, the following visualisation shows the relationship between topic allocation and sentiment. We can see that Topic 1 contains a higher proportion of positively scored texts, whereas Topic 2 contains a higher proportion of negatively scored texts.

In the next, we can see Topic and Sentiment scores combined with the Time at which each tweets was made. Those closer to 8am appear on the left-hand-side, moving towards 8.30am on the right-hand-side.

We can remember from the Topic allocation at the words Spotify and Radio appeared frequently, so we may want to compare the results of analysis in these terms. In the visualisations below we can see different combinations of analysis based on stories that contain the word Radio and Spotify.

Correlations

Another potentially interesting thing to look at once we have generated additional numeric variables is to see if there is any statistical relationship between them. Again, with such a small data set we would not expect to see anything of great significance, but in order to demonstrate the process here is a correlation matrix based on the additional variables created.

Discussion

The abstraction of complex, real world activity into data points on the one hand makes analysing large collections of texts more manageable, but on the other it can often produce results that can be misleading – think, for example, of the ‘angry’ tweets above. This means that we should always question both the process and the results of that process.

Using computational processes to analyse and explore text-based corpora is an interesting route, but it is not without significant issues. In the first instance, and speaking from my own experience, learning how to perform analysis of this kind is tricky and time-consuming, particularly when – as in my case – the researcher does not come from a computational background. I have learned (and am still learning) how these process work. This, I think, is representative of a wider questions in the humanities when it comes to work of this kind: where scholars are attracted to the affordances of large datasets and computational techniques through their increasing availability and falling barriers to entry, but are simultaneously ill-equipped to use them adequately, fully understand the results, or usefully explain the nuts and bolts of the methods of analysis used once such techniques are deployed. Through sharing these works-in-progress and I am attempting to contribute to Sandvig and Hargittai’s recent call for academics to share the details of their ‘messy’ benchwork following attempts to put such techniques to use. The desired outcome, they say, is a space where ‘researchers can reveal the messy details of what they are actually doing, aiming towards mutual reflection, creativity, and learning that advances the state of the art’.

Resources

The post is accompanied by a sample data set and R script. If you would like to replicate the work shown here you will need the following:

Harkive day 2017 has now ended. Thank you to everyone who told their music listening stories and to those who so kindly helped to spread the word about the project. As has been the case in previous years, it was a hugely enjoyable thing to run and the response was great. I hope that you enjoyed taking part also. Let’s do it all again next year!

I’d like to ask one more thing of you before you go….

The 2017 Music Listening Survey

I’d like to invite you to complete the 2017 Music Listening Survey, which takes around 5-10 minutes to complete. This asks questions about your music listening generally and your participation in Harkive. The data gathered by this survey will be crucial at the analysis stage of the project as it will provide important contextual data for the stories you have told. If you completed this survey in 2016, please do consider having another go. It will be interesting to see how responses have altered over the last 12 months.

You can still tell your story

If you didn’t manage to tell your story yet but would like to, remember that you can still email it to us, or use the form on the project site. Have a look at the instructions on the How To Contribute Page for more information. Story entries will be accepted until midnight (GMT) on 1st August 2017.

What happens Next?

The stories gathered yesterday will be collated, the data will be sorted and cleaned, and I’ll then have a better idea of the amount of stories received. I’ll post details of those numbers in the next week or two, but a conservative estimate at this stage is that their would appear to be in the region of around 1,000, which is about on a par with previous years.

Once the data is cleaned and sorted, and the results are gathered from the Listening Survey, the data will be added to that gathered in previous years and further analysis can begin later in 2017. In the immediate near future, I have to complete my thesis before the end of September and, as I’m sure you can understand, this will take priority. After that, though, I’ll be working on producing some online visualisations and interfaces that will display the stories and data gathered since 2013, along with the results of my analyses. Details of how that is progressing will be posted to the blog and links will be shared on Twitter and other social media channels. If you’d like to be involved with the analysis, or would like to collaborate with the project in some other way, please do get in touch.

Harkive is an annual online popular music research project that invites people to tell the tale of How, Where and Why they listen to music on a single day each year. The aim of the project is to capture for posterity a snapshot of the way in which we interact with the sounds and technology of today.

On Tuesday 25th July we hope you’ll join in by telling Harkive the story of your music listening day.

In this quick guide, you’ll find everything you need to know about joining other music fans around the world on 25th July. We’d like you to help us add to the 8,000 stories gathered by the project since we launched in 2013.

Why tell your story?

Millions and millions of people will be listening to music on 25th July, but no two people will listen in precisely the same way, or for the same reasons. That makes you interesting.

You might use certain products, services, formats and technologies that are common to many others. You might spend the day listening to the same radio station as millions of others. You might go to a gig, or hear music in a restaurant, or catch the hint of a song from the window of a passing car. Whatever your experience, or the situations you find yourself in as you listen, what happens will be unique to you. It is the unique nature of your story that we are trying to capture.

How, Where and Why you listen to music is fascinating – we’d like you to tell us all about it.

How to tell your story

Telling your story is easy, and you can tell it in a variety of ways. Hopefully there is one that suits your habits already, and you won’t need to go too far out of your way to do it.

You can post to social media platforms, such as Twitter, Instagram and Tumblr, simply by adding the #harkive hashtag to your posts throughout the day. Or you can ‘like’ the Harkive Facebook page and post something to our wall. You can post as many times as you like across the day.

If you’d like to take your time and write something a little longer, you can email your story to us, or post it via our online form.

A full list of the ways you can tell your story is available on the How To Contribute page.

What do Harkive stories look like?

The stories the project receives come in all shapes and sizes, from short tweets to long-form essays. The shortest story in the database has just 6 words, the longest has almost 4,000. We’ve already had our first story of 2017, which came in via Twitter from Auckland, New Zealand just after midnight local time – have a look.

For further inspiration, have a look at some of the Example stories we’ve gathered from musicians, journalists, academics and others in recent years. For some more examples, here is a slideshow of some extracts from stories gathered since 2013 – flick through to see how people have told their stories. Remember, though: there is no right or wrong way to tell your story. Just tell us in your own words about the role that music plays in your day on 25th July.

Have a look around online and get involved

Many regular Harkive participants comment that one of their favourite things about the day reading the posts of others, or joining in with conversations with other participants. Some even discover new songs through the project. Have a look on Social Media channels (especially Twitter, where most of the action seems to take place) by searching the #harkive hashtag.

If you do make some discoveries, and just for fun, why not add them to the 2017 Harkive Collaborative Playlist on Spotify. Click here to view that.

Can you tell us more?

For 2017 we also have a Music Listening Survey. This takes around 5-10 minutes to complete, and will provide the project with some additional context about your music listening that will be crucial to the research that underpins this project (more on that below). Whether or not you intend to join in with Harkive 2017, please do take a moment to complete the survey.

By way of background, we road-tested this survey last year with a UK-based vinyl and CD manufacturer. Their staff completed the survey and produced this beautiful infographic. We’d love to include your responses in something similar.

What happens after Harkive 2017?

Harkive will return again in 2018. In the meantime it forms the basis of a PhD research project at Birmingham City University by Craig Hamilton. Shortly after Harkive 2017, Craig will complete his thesis. Information about any publications or conference papers that emerge from this research work will be posted to this site, and via the Harkive social media channels. By collecting Harkive stories through digital channels, Craig’s research is able to explore computational methods of analysis as a means by which to examine the role that digital technologies play in contemporary experiences of popular music.

What happens to my data?

This project has been approved by Birmingham City University’s Research Ethics Committee, and for more information on that please see our Research Ethics statement. None of the personal information (email addresses, etc) provided by you to the project will be made available to 3rd parties without your consent but elements of stories may be shared via an API research tool currently in development. Please feel free to contact us if you have any questions related to this.

Please help us spread the word

We’d love to hear from as many people as possible on Tuesday 25th July, so if you think the project is interesting, please do tell your friends about Harkive and encourage them to join in. You can share this post with the following link: http://harkive.org/h17-welcome/

Ask us anything

If you have any questions about Harkive, or would like some guidance about how to tell your story, please feel free to email us, or say ask us on Twitter, where we are @harkive

We’d love to hear your story on Tuesday 25th July. Please do join us by telling Harkive your story.

Harkive is an annual online research project that gathers stories about How, Where and Why people listen to music across a single day. The project this year takes place on Tuesday 25th July – We’d love to hear your story.

The project is interested in how music plays its part in your day on 25th July. We’re interested in the technologies, formats and services you use, the places you find yourselves in and how music accompanies you as you move through your day, and – of course – how music makes you feel.

Joining in with the project is easy. You can do so simply by adding the #harkive hashtag to your music-related posts on Twitter, Instagram and Tumblr. Alternatively, if you want to write something a little longer, you can email it to us, or send it via this online form. Stories are also accepted as posts on the Harkive Facebook wall.

You can send as many entries as you like across the day, and you can write as much or as little as you like. Feel free to include photos, links and other digital media. There is more detailed information on how to tell your story here.

Harkive is part of a PhD research project. You can read more about the background of that here, and find more detailed information about the research ethics of this work here. To further aid the research process, there is also an online survey. It takes around 5-10 minutes to complete, and you can do this before or after 25th July. If you do not wish to complete the survey, don’t worry: you can still contribute your story on 25th July.

We’re pleased to announce that Harkive 2017 will be taking place on Tuesday 25th July.

Since launching in 2013, this annual popular music research project has gathered over 8000 stories. Once again, Harkive will be attempting to mobilise music lovers around the world and we’re inviting you to join in by sharing the story of how, where and why you listen to music on 25th July. By gathering these stories Harkive hopes to capture for posterity a global snapshot of the way in which we interact with the sounds and technology of today. We hope you’ll consider joining in on the day.

You will be able to tell your stories to Harkive on 25th July in a number of ways. You can email the project directly, post to social networking sites such as Twitter using the #harkive hashtag, or on the wall of the Harkive Facebook page, or you can submit audio, photos, or video. A full list of the methods of how you can contribute are listed here.

On Tuesday 25th July the world will be listening. We do hope you’ll get involved and tell us your story.

One of my favourite things to do is buy music. I rarely pass up the chance to mooch through the racks of record shops, or charity shops, or indeed any shop where I might pick up a bargain. I’ve been doing this for over 25 years and I recognise that it’s probably something of a compulsion by now – mostly it’s about a love of music and a desire to add to my collection, but a good deal of it is just plain old habit. A regular conversation between me and my wife goes something like this:

Me: “I just bought this for £2. It’s worth about £25”

My Wife: “Ok, but you’ll never sell it, so it’s worth -£2″

She has a point, of course. Although I’ll periodically have a purge and clear out some records, the majority remain on the shelves in the front room of our house and are slowly colonising our living space. I’ll probably never stop.

I’ve always bought a lot vinyl records, but have recently found myself buying CDs for the first time (they are ludicrously cheap in charity shops these days) and a year or so back I bought a gramophone (£10 on eBay!) so have also been picking up a few 78 rpm discs.

On Christmas Eve last year during yet another ‘quick look’ around charity shop, I bought more records. As I’d been experimenting with data analysis in R as part of my PhD research and was looking for projects to work on, I decided that I would begin keeping a record of everything I bought from that point on with a view to running some analysis on my habit. Mainly I wondered how much I spent doing this – £1 here, £5 there on a regular basis probably added up to a frightening amount, I figured, but I was also curious as to how often I bought records, where, in what volume, and also whether I was unearthing buried treasure or just buying rubbish.

To help find out the answers to these questions I started a spreadsheet where I recorded the things I bought, along with the price I paid, the format the music was on, whether the item was new or 2nd hand, and where and when I bought it. I also started adding the purchases to Discogs (something I plan to do with my entire collection at some point) and as I did that I made a note of the Median Sales Price each of the items fetched in the Discogs marketplace. This enabled me to arrive at a rough calculation of how much I was ‘up’ in a purely theoretical sense (since, as we’ve established, I’ll never sell the majority of the things I buy). Clearly this is not a precise measurement as there are lots of other factors to consider in terms of the actual value of items – condition of the record/sleeve, fluctuating prices in the marketplace, and so on – but as a general rule of thumb it seemed like a useful barometer.

Here are some basic insights from the data I’ve collected so far. The following includes the handful of records I purchased in the last week of 2016, which have been lumped in with the 2017 purchases.

– The average amount spent on per item was £3.17. Excluding new purchases this fell to £1.99 per item.

In terms of when and how many, it appears that I’ve bought 4 or more items each week in every week except for two so far this year. The spike around the middle of January coincides with my birthday, and this was when I spent some Amazon vouchers I’d received as gifts. Over my birthday weekend I also found a pile of 78 rpm records in a junk shop (more on those in a moment), which contributes to that splurge.

In terms of my making a ‘profit’ from digging around in record shops, the data from Discogs is reasonably pleasing (caveats above notwithstanding).

– The £199.80 I’ve spent equates to a possible/theoretical £466.62, which means I am ‘up’ by £266.82

– The average Discogs sale price was £7.40 (compared to £3.17 purchase price), which is an average ‘profit’ of £4.23 per item.

The following chart shows price paid against Discogs ‘value’, with the average line indicating that in all but a couple of cases I’ve managed to pick things up for less than they are ‘worth’. You’ll notice that the majority of new items (shown as triangles) have roughly the same purchase/sale price, but it’s reasonable to assume this will change in my favour over time. The further items are away from the black line indicates a bigger difference between purchase price and potential value. The two dots on the bottom right hand corner are a Beach Boys CD boxset I picked up for £4.99 that sells for around £20, and a vinyl copy of Crowded House’s ‘Woodface’ that fetches around £25 that I got for £3.

From Discogs I also recorded the year of release for things I’ve purchased, and this combined with formats and prices/’profit’ makes for another interesting visualisation that gives some insights into my hoarding habits and the current marketplace for digging around in charity shops and junk shops.

– 78rpm records are mostly very cheap, and mainly because most of them are rubbish, but if you choose wisely you easily can pick up things that are worth £5 or more. The best I did here was a copy of The Andrews Sisters’ ‘I Saw Mommy Kissing Santa Claus’ in it’s original picture sleeve, which I picked up for 35p and which could sell for around £15.

– CDs from the 1990s and 2000s are very cheap at the moment – you can pick them up for as little as 25p in charity shops – and although the majority are worth what you pay for them, some are surprisingly sought after. I got a copy of Exotica ’92 – a collection of novelty football records – that is worth upwards of £10. Based on this small dataset, it appears that 1990s CDs are worth picking up at the moment.

– It looks like I buy a lot of 1960s and 1970s vinyl, but very little from the 1980s. This would fit with my general tastes, I think, but it now has me wondering whether I should address this gap (…oh dear).

– Good stuff on vinyl from the 1990s onwards is unsurprisingly thin on the ground (there was less of it about, for a start), but it’s worth picking up if you see it. The 1991 Crowded House record I mentioned before is the big pink dot towards the top of the picture.

This is as far as I’ve managed to dig so far into the data, but I’ll be adding to the 63 items over the course of the year and will be working on some other analysis. Once I have some more/better analysis I’ll provide code and sample data so that you can adapt and use for your own purposes, should you wish to explore your own habits.

One thing I would like to try is to combine this data set with my Spotify audio scrobbles that I collect from Last.FM; it would be interesting to see how my record/CD buying influences my listening on digital services, and vice versa. I’ll post on that soon.

In this blog post and accompanying video I will attempt to explain the process of performing some basic encoding and visualisation on survey data using the R package. The data and R scripts used in this example post are available to download via the Harkive GitHub repository.

I hope to show how survey data can be relatively easily visualised using the R package in order to help deliver potentially useful insights. In the example image below, generated using the scripts and data provided here, responses to questions about the importance of Cost when choosing regularly used formats for listening to music are plotted against the importance of Convenience.

What is perhaps unsurpising is that the majority of the people in the random sample set consider both to be important. Perhaps more interesting, however, and certainly in terms of selecting subjects for further analysis, are those who appear to consider neither as important. It leads us to ask further questions as to why that would be the case, and what are important factors to those people. The broader point here being, these are observations and questions that a relatively quickly constructed visualisation can afford us – it would be extremely difficult to observe what we can see here from simply looking at the original data set.

The intention of publishing this data/code is thus twofold:

1) As I have benefitted hugely in my own learning from the culture of sharing data and code that surrounds R, by sharing this code and data I hope to provide some assistance to researchers seeking to analyse their own survey data but who are, like me, new to R. The scripts provided here should be relatively easy to adapt to a different data set, if that is your aim.

2) I also share the data I have gathered in the hope that more experienced researchers and/or those with an interest in popular music may develop their own analyses and share their results/code with us. There are responses to 90 different questions related to popular music listening within the data set – offering the possibility for a huge number of ways in which the data can be analysed. It would be very interesting to see what others come up with using this data. Please do feel free to adapt, create and share your thoughts.

Background

Harkive has been collecting stories from people online about their music listening experiences on single days in July since 2013. Stories are collected from various social media channels (Twitter, Facebook, Instagram, Tumblr) and also via email and through a form on the project website. In order to assist with the analysis of these stories, a Music Listening Survey was devised in 2016 that aimed to gather additional information from participants. This survey was open to both participants and non-participants of the story gathering element of Harkive. Analysis of the data gathered by the survey is intended to:

provide insight into the experiences of popular music listeners

contextualise the individual text-based stories gathered by Harkive

enable the sub-setting of the entire corpus of stories based on observations gleaned from the survey data

The survey is still live and responses are still be collected, so if you would like to participate you can do so by visiting http://www.harkive.org/h16-survey . It would also be hugely appreciated if you would share this link with other music lovers.

The Data

The Harkive Survey was created using the JotForm service and then hosted on the Harkive site. After providing their informed consent and some demographic information, participants were then asked whether they had participated in the story gathering element of the Harkive Project (those who indicated that they had were then asked to provide further information about this). Participants were then asked to respond to 86 questions/statements regarding their music listening. In the main, these required responses along Likert Scales. For example, participants were asked to rate whether they Strongly Agreed or Strongly Disagreed with a statement along a 7-point scale.

Data was downloaded from Jotform in CSV format, and a sample of 100 anonymised responses are used here. This sample is comprised of 50 responses where people had indicated they had participated in the story gathering element, and a further 50 where respondents indicated that they had not. Other than that, data was selected at random.

The R Scripts

There are two R scripts that accompany this post. The first takes the ‘raw’ data downloaded from JotForm and converts text-based responses into numeric values. Using these newly created numeric responses, additional variables are created that provide summaries of sections. The second script uses the numeric values created in the first to create some basic visualisations that enable some initial analysis of the data within the survey. By following through both scripts you will be able to replicate the image displayed at the top of this post, and by adapting the code provided in the script you will be able to visualise and explore the rest of the dataset.

For new users this may sound daunting, but the video links above are very helpful and should have you up and running in a few moments.

The Video

Here is a 30-minute screencast in which I walk through the two R scripts provided. Hopefully those of you who are new to R will find it useful in terms of adapting the scripts, and those of you interested in performing your own analysis of the data will get a feel for what it contains.

Discussion

I am by no means an expert when it comes to creating R scripts, or in Statistical Analysis. More experienced R users may indeed find the way in which I have structured these scripts to be cumbersome and inefficient, and there are probably mistakes in my descriptions and scripts. I am still very much in the early stages of learning R, and as such these scripts are presented in much the same way that I am attempting to develop my skills: through a process of trial and error, one that is iterative and exploratory.

What is useful about that, from the point of view of my own research, is that it has necessarily forced me to break down analysis into discrete component parts. I have learned one step at a time. This not only makes the research replicable both for me (once I learn how, for example, how to visualise one set of data, I can quickly apply that to another) but also potentially others (in that fellow researchers using their own Survey Data may be able to build on this work) but, perhaps more importantly, the assumptions inherent in each step are revealed more clearly.

The act of assigning numeric values to Likert Items, such as I have here, is a case in point. This is heavy with a number of assumptions: that Person A meant the same thing as Person B when both said “Strongly Agree”; that the distance between “Often” and “Very Often” is exactly the same as that between “Rarely” and “Never”, and so on. Further to that, once data of this kind is visualised in a coherent form (as I have attempted to do here), then inferences and insights are ‘revealed’ more starkly. As we will see in later posts, where I will take the insights revealed from survey data and apply them to the corpus of Harkive stories, the research process itself thus becomes a creative act just as much as it is a logical, empirical one. One should always remember, then, to consider both the provenance of the ‘raw data’ (a questionable term, as Gitelman argues) and the process through which that data has ultimately led to insight. As numerous scholars working in this area have argued, reflexivity is as crucial an element as the technical skills required when undertaking work of this kind.

The beauty, then, of an R script and other computational analytical processes, is not only in the efficiency and logic they afford, but in the way they isolate and force us to confront the assumptions inherent in our work.

In this blog post I’m going to attempt to explain the process I use to collect data for The Harkive Project, and how collecting it in the manner that I do considerably helps reduce the amount of time required in organising and cleaning data ahead of analysis. The resulting database created by this process is organised according to the principles of Tidy Data, principles that are extremely useful when using the R package (as I am) as the primary means of data analysis. Hopefully you may find this post and the accompanying video useful if you are considering using social media and/or other digital data in your own research projects.

It should be noted at the outset that Harkive as a project has specific needs in terms of data collection, and the process I will describe has been devised with those in mind. This necessarily means that the process I use may not be entirely replicable for your own needs, so I will instead attempt to explain in terms of general principles and tasks so that it may be useful to you with some minor adjustments.

Before I begin, and for those of you reading this who may be unaware of The Harkive Project, I will provide a little context and background that may be useful. Following an explanation of the process, I have included some general discussion about the process and its limitations.

Background

Harkive is an online research project that seeks to gather information from people about the detail of their engagement with popular music on a single day each year. Since 2013 the project has operated on a day in July, and participants are invited to tell the ‘story’ of their music listening day by either posting to social media platforms using the #harkive hashtag, emailing the project directly, or by completing an online form. When the project ran in the years 2013-2015, I used a combination of different techniques to get the data from various sources that resulted in several different databases, each organised according to different schema. I was particularly grateful to Martin Hawksey and his work on TAGS, which enabled me to gather data from Twitter. By using GoogleDocs I was able to create and embed a simple Form on the project website to capture ‘stories’ there, as well as through emails sent to the project. For most other services, I used a combination of IFTTT recipes.

Whilst these separate collection techniques all worked well in isolation, it left me with data in several separate spreadsheets, each of which were organised according to different schema. This meant that a period of data sorting and cleaning was required to get data from different sources into a single spreadsheet before analysis could begin. This was time-consuming and error-prone. Following discussions with my BCU colleague, Nick Moreton, we began to investigate the Zapier service as a means by which to collect data in a manner that also sorted and organised it, thus making the entire process more efficient

Video

Here is a video that walks through the process described below.

General Overview of Process

As with a number of other services, Zapier will enable you to connect to the APIs of a number of different 3rd party online platforms, including Twitter, Tumblr, Instagram, and then collect data from these based on a specified searches, or other conditions. Zapier can also be used to extract data from emails, forms and other online media.

In order to do this via Zapier you create a separate ‘Zap’ for each service/place that you wish to collect data from. During the creation of ‘Zaps’ you are be able to specify which elements of the third party APIs to collect data from, which means that you can discard elements you do not need.

Each Zap can be augmented by adding additional steps that allow you to write the collected data to a specified location within a database of your choice. Common elements from different services (for example, usernames) can thus be written to a single username column in a destination database, even though the naming conventions and/or data formats of those datapoints may differ from one API to another.

Adding a fixed variable to each ‘Zap’ – such as one that specifies the source of each entry (e.g. Twitter, Tumblr, Instagram) in the example below – will write a separate column in the destination database that records this fixed variable in each row.

Likewise, fixed variables denoting NULL values can also be added where the API of one service does not provide an element that is present in another. For example, Tumblr and Instagram provide tags (hashtags) added by users as elements of their APIs, yet Twitter does not. By giving a NULL value to the tags element of the Twitter Zap, whilst adding the relevant tags elements to the equivalent variables in the Instagram and Tumblr Zaps, the column in the destination database is populated with either a true value, or a NULL value.

These NULL values become useful when a present variable in an API is not populated by a user. For example, if a Twitter user does not add an image to their post, but you are collecting that element, the Zap will populate the database with a blank value. Blank values (not present) can thus be differentiated from NULL values (not available).

Additional steps can also be added that can pre-process certain data before it is written to the destination spreadsheet. This is particularly useful in terms of Date and Time stamp formats, which often differ from service to service.

The process will involve some trial and error, but eventually you should end up with a single spreadsheet of data collected from numerous sources that contains data organised and formatted according to a schema of your choice.

What You Will Need To Get Started

An account with Zapier.com

Accounts on the Social Media channels you wish to collect data from

A Gmail account

For ease of set up I recommend that you log in to each of the relevant services above, and have each open in separate tabs within your browser before proceeding with this workflow.

For the purposes of this simple example we will collect data from Twitter, Tumblr and Instagram, and will limit our collection to just the usernames of posters, the text of their posts, and date/time stamps. Adding additional variables is simply a case of extending the process described below.

Step 1: Creating A Schema

Within GoogleDocs (or similar) you need to create a blank spreadsheet into which Zapier can write the data collected from different services. The aim here is to create columns within this sheet into which common data points can be written. For the purposes of this example, create four columns and call them service, user_name, text, and date. Name your new spreadsheet zapier_test.

Your new, blank spreadsheet should look like this:

It may sound slightly counter-intuitive to suggest creating this step first, since you will not yet know what data are available from the different services that you wish to collect from, or where commonalities occur. This is where the Trial and Error element comes in and you may need to add or remove columns until you get the right API elements into the right columns.

Step 2: Creating A Zap

You now need to create separate Zaps for each of the three services (Twitter, Tumblr and Instagram). Let’s set up Twitter first.

Click on Make A Zap on the main dashboard, search for and select Twitter as your Trigger App, and then follow through the steps prescribed by Zapier to authorise it to access your Twitter account. After that, specify your search term. Finally, test the collection of Twitter data based on that search. If the test is successful, you will be able to view the different elements of data returned from the Twitter API. The elements that we want to capture in this instance are: user__name, text & created_at, which are those that correspond to the user_name, text and date elements of the destination spreadsheet, zapier_test. Make a note of these as you will need them in the next step.

Next, and still within the Make A Zap window, you need to add the step that will write data to your newly created GoogleDocs sheet, zapier_test. Select ‘GoogleSheets’ from the available dashboard, and then the radio button for ‘Create Spreadsheet Row’, and (after authorising your GoogleDocs account) you should select zapier_test and Sheet 1 from the pull-down menu. If it doesn’t appear, use the search option to find it.

You can now add the elements from the Twitter API to the required fields in the spreadsheet, like in the image below. Note that we have added twitter as a ‘constant’ entry.

NB: The first time you set this up you will need to follow the instruction that allow Zapier to write a test row to the spreadsheet before continuing. This is to test Zapier’s ability to write to the spreadsheet. You will only need to do this once.

Once completed click ‘Finish’ and then ‘Name Your Zap’.

You can now repeat this process for Tumblr by returning the beginning and selecting to Make A New Zap. After selecting Tumblr as your Trigger App you will notice that the option to search on a specific term is not available in the same way as it was through Twitter. The closest equivalent in Tumblr is to search for tags added to posts. This is will be discussed further in the discussion below, but it is an inherent flaw in collection methods of this kind and ultimately relate to the fact that you can only perform tasks that are permitted by the 3rd party concerned.

The elements of the Tumblr API that match those that we want to gather from the Twitter API are as follows: blog_name; body; date. As before, we also add tumblr as a constant on each entry.

Repeating this step for Instagram (which like Tumblr requires that you search on tags, rather than search terms) results in the following:

Once you have completed the process of setting up this third Zap, and depending on the frequency with which your search term is used by posters to theses three services, you will then begin to see your zapier_test spreadsheet begin to update with new entries.

Pre-Processing Data

You may wish to add some pre-processing to the steps you add to your Zaps in order to render data in a united format. The collection method described above is collecting Date/Timestamps from each service. However, these appear in different formats.

Twitter API date/time format: Fri Jul 09 09:51:53 +0000 2010

Tumblr API date/time format: 2015-10-27 07:13:17 GMT

It is therefore useful to convert these to a common format before writing to the zapper_test spreadsheet.

NB: You may need assistance from someone versed in javascript to achieve this.

To change date formats to a common one, revisit your zaps individually to add an additional step between the existing steps. To do this click on the + icon between the Twitter and Google Sheets elements. Once you’ve clicked on the + icon, select Action, then Code by Zapier. Finally, select that you wish to add some Javascript. Your screen should resemble this:

This next step is the Edit Template, which will apply the necessary changes. We’re applying the javascript to the created_at element, which converts Twitter’s API date format.

You will need to apply this step to your other Zaps (for Tumblr and Instragram), using amended javascript each time to alter the date/time formats to your desired format. This function, of course, can be applied to other elements your Zaps collect.

Discussion

I am by no means an expert when it comes to either tutorial production or social media data collection. However, I have found that this process is suitable to my own research needs (although not without issues – which I shall highlight below). If you have any questions, corrections or other comments about this post and/or video, please do get in touch and I will attempt to assist you. If you have found it useful, please also feel free to share, adapt, build upon or otherwise repurpose elements of it.

You should be aware that Zapier offers tiered subscriptions based on usage. Although the free tier may be suitable for your needs, if your research project has the potential for the collection of a large amount of data, you should consult their documentation on pricing before proceeding.

The process described above contains within it the potential for fragility because it relies on the availability of data from the owners of 3rd party platforms. As boyd and Crawford observe, ‘data companies have no responsibility to make their data available, and they have total control over who gets to see them’ (2012). The data available via APIs is thus limited and subject to change at any moment, and as such you are advised to monitor the collection regularly to ensure that you are capturing what you expect to see. As boyd and Crawford also observe, it is not clear and indeed largely impossible to discover, whether the process described above is capable of capturing everything posted, or just a sample. Tweets, for instance, from accounts where users have instigated privacy settings (known as ‘protected tweets’ in the language of Twitter) are excluded from searches of this kind and so will not be collected. Therefore, data collected in this way can only ever be described as a sample, rather than the entirety of posted data. This issue highlights the caution that many scholars have in terms of using Social Media data as representational of human behaviour and experience.

In addition to the fragility of the API-derived data, there is also an issue with the manner in which the availability of data necessarily directs the methods by which researchers are able to collect data. This is evident in the workflow above, where the manner in which data is searched differs from service to service. The Facebook API, not covered in this post, is also a case in point. This will only collection of data that is posted by a user to a specific page. Anything posted to the user’s own timeline is not collected. This clearly differs from the main means by which many users engage with Facebook – i.e. through their own feed, not the pages of others. As such data collected from Facebook (and other sources) needs to be considered in terms of its limitations, and not just affordances of the relative ease by which it can be gathered.

Closing Remarks

I’ve been meaning to post this workflow for some time, but a couple of things have made it expedient to do so now. In the first instance I’ve recently completed a first draft of the methodology chapter of my PhD thesis, so this (and other) practical elements of the project are the things I’m currently thinking through in detail. The word-count constraints of a PhD thesis do not really allow for the inclusion of finer details about processes such as that being described here, so this and subsequent posts are intended as appendices of sorts. Further to that, next week I’ll be part of a panel at an event at The British Library that is looking at how non-text outputs of PhD and other academic research projects can be helpfully made available via the EThOS system. Although this post is quite clearly predominantly text-based, I would nevertheless include in the general category of non-text outputs that I am producing through my research, alongside such things as datasets, visualisations, R scripts, and other elements that do not necessarily fit into a ‘traditional’ format of a thesis. Finally, a group conversation that recently took place on the emailing list of the AOIR, of which I’m a member, suggested that sharing this workflow may be useful to others. This, I feel, is an important point more broadly and relates to my interest in the ETHoS project: the results or outcomes of research (commonly referred to as Impact in academic circles) have the opportunity through mediums such a blogs and other digital repositories to be potentially useful outside of the context of the original research, particularly when elements of a larger methodological processes can be isolated and presented as general guides. Sandvig and Hargittai have argued recently that the ‘workaday’ practice of the humanities/social sciences research process needs to be highlighted, particularly in areas of work that look at digital media and the Internet, because these are producing ‘new methods, new opportunities, and new challenges for understanding human behaviour and society.’ As such, this post will be the first in a series of ‘practical’ posts that I hope will make a small contribution to that and may prove to be useful.

Harkive day 2016 has now ended. Thank you to everyone who told their music listening stories and to those who so kindly helped to spread the word about the project. As has been the case in previous years, it was a hugely enjoyable day for us, and we hope you enjoyed taking part. We’d like to ask one more thing of you before you go….

It takes around 5-10 minutes to complete, and asks questions about your music listening generally and your participation in Harkive. The data gathered by this survey will be crucial at the analysis stage of the project as it will provide important contextual data for the stories you told. Please do take a look:

The stories gathered yesterday will be collated, the data will be sorted and cleaned, and we’ll then have a better idea of the amount of stories received. We’ll post details of those numbers in the next week or so, but a conservative estimate at this stage is that their would appear to be in the region of 1,000, coming from places such as Australia, India, Japan, the UK, Germany, Spain, Norway, USA and others. Once the data is cleaned and sorted, and the results are gathered from the Listening Survey, the analysis stage will begin. Details of how that is progressing will be posted to the blog and links will be shared on Twitter and other social media channels about that. If you’d like to be involved with the analysis, or collaborate with the project in some other way, please do get in touch.

You can still tell your story

If you didn’t manage to tell your story yet but would like to, remember that you can still email it to us, or use the form on the project site. Have a look at the instructions on the How To Contribute Page for more information. Story entries will be accepted until midnight (GMT) on 28th July 2016.

Harkive will be back again next year, on another sunny day in July, for what will be our 5th year. Please do join us again. In the meantime, Harkive will be posting stories throughout the year here on the project site and will be releasing new episodes of the Harkive Podcast. If you’d like to suggest stories for the site, or themes for the podcast, drop us a line or say hello on Twitter. Stay tuned, in other words.

One of the main challenges of the PhD project that Harkive is part of, is the need to devise a means by which the insights held within the stories people have told the project since 2013 may be revealed. The largely text-based data collected represents a huge challenge in that regard, leading to a methodological focus on collaborative and experimental analytical methods. Such an approach is by no means unique to this project. Academic researchers in a number of disciplines have been embracing new methods and experimental approaches for several years, leading to the genesis of entirely new fields: Social Computing; Digital Humanities; Cultural Analytics. At the same time, barriers to entry and access in terms of data collection, storage and analysis, are falling, enabling people to critically and artistically engage with data in interesting ways. Think of terms such as Citizen Data Science, or movements such as The Quantified Self.

Harkive and the doctoral research project that underpins it, resides somewhere within the broad and emerging area described above. What makes this exciting for the project is that, just as the landscape of modern popular music is a fascinating and dynamic space, so – increasingly – is the field of human-data interaction.

To put all of this another way, just as the stories Harkive collects are ‘crowd-sourced’, one avenue this project is keen to explore is to see if perhaps some of the analysis may come from a similar method. What questions would other people like to ask of this data? What could be built with it? What would it sound like as a piece of music? These are the questions that come from having an inquiring mind and an interesting data set! There are more possibilities and questions than there is time, however, and it is with this in mind that we have created the Harkive API, full details of which are provided below.

For those of you reading who may be unaware of the function of an API (Application Programming Interface), in simple terms it allows access to data in a structured, reliable way, so that applications, visualisations and other online tools (and even pieces of music) can potentially be created by making use of the data. The crucial point is that although the data held within an API may change over time, the structure the data is held within remains constant. This means that anything built upon an API is able to change dynamically in line with changes in and to the data, without necessarily having to change its own structural dynamics. APIs are thus powerful tools for developers and, increasingly, academic researchers.

Data Visualisations created with Harkive API

A better way to understand the above is to look at the small number of visualisations that have been built by Nick Moreton using the Harkive API. These are being hosted on a dashboard at www.harkive.com and relate to the Harkive 2016 data. This data is and will be dynamic – as people tell their stories, they will generate more data – but the structure of the API remains the same. Because the visualisations on www.harkive.com are built with the API, they will change as more stories are gathered.

Here are some examples:

Story Sources: will display the ratio of total stories according to the various submission methods. For a full list of the available story-telling methods, please visit the How To Contribute page. From the screenshot below, it is easy to see the dominance of Twitter in terms of conversations about Harkive, but these ratios may change on 19th July as stories begin to be posted elsewhere.

Harkive Around The World: will display details of Tweets sent with the #harkive hashtag, where Twitter users have enabled location settings.

WordCloud: Following automatic removal of Stopwords and other phrases (incl. the word Harkive, which features prominently in collected posts), this visualisation will produce a Wordcloud based on the content of Harkive stories. As the screenshot below shows, ‘tell’ is a prominent word at this point in time, and this is because of the promotional posts (and shares of those posts) encouraging people to ‘tell their story’ to Harkive.

The basic examples above demonstrate some of the many ways that different levels of insight can be derived from data. They represent, however, only the tip of the iceberg of what is possible.

Shortly after the 2016 story-gathering element of the project ends next week, we will begin the process of sorting, cleaning and analysing the data. For the purposes of the immediate concern of the PhD project Harkive forms the basis of, this analysis will proceed according to three broad themes: Formats and Technology; Data, Privacy, Identity and Ownership; Recommendation and Discovery.

If you would like to get involved with this process please do contact info@harkive.org. There are already a small number of academic researchers, analysts and data scientists working on ideas for the data, so please do consider collaborating with us.

If, on the other hand, you would simply like to play with the API and the data it contains in order to create something cool – perhaps even a piece of music? – then please do so. Just remember to let us know what you come up with so that we can share it with the wider Harkive audience.

The Harkive API allows developers access to limited elements of the data collected by The Harkive Project. In particular, and based on the Research Ethics underpinning the project, the API does not provide access to personal information gathered by the project.

The API currently contains only stories collected by the 2016 instance of Harkive. Stories from 2013-2015 will be retrospectively added shortly after Harkive 2016.

The automated collection methods that place new data within the API structure at present capture everything related to Harkive, so will necessary include tweets (and other types of posts) that mention the project. Although tweets sent from the official @Harkive twitter account have been excluded from certain counts in the visualisations, anything posted by others online ahead of Tuesday 19th July will be displayed. This data is included at this stage primarily to demonstrate the API and visualisations. Shortly after 19th July, data contained within the API will be sorted and cleaned, leaving only stories.

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story. You can read our quick guide to the project here.

We’re now on the final countdown to Harkive 2016, with just 1 day to go. As we have done in previous years, in the run up to the big day we’ll be posting some ‘example’ stories from people who do interesting things with their music listening. Today, for our final Harkive 2016 example we welcome Juice Aleem.

A mainstay of the UK hip hop scene, Juice has released singles and LPs on NinjaTune and Big Dada, collaborating and touring with the likes of Luke Vibert and Coldcut along the way. He returns with a new LP in 2016, “Voodu Starchild”, featuring contributions from Mike Ladd, Roots Manuva, Blackitude and more. Lead single “Warriors” is available as a free download from label Gramma Proforma here.

Juice kindly agreed to tell Harkive the story of his music listening day, and here it is.

Music is a thing that has always been there for me.

Certain feelings and memories of mine are placed in the context of songs or genres that have moved me. Moving me.

Preparing to move house again brings on a lot of reflection. And in that sense, there are tunes that will always transport me to other places, reminding me of friends, family and lovers.

Gil Scott Heron’s ‘The Bottle’ will always take me the ‘Rare Groove’ era of places such as West End Bar in Birmingham. Searching for these records and really having a ‘discovery’ of artists that were not only as exciting as the current scene but also had immense amounts of back catalog was really a joy.

The joy would make us feel connected to a deeper history of popular culture, like we were more clued up than everybody else. That special energy of youth is fueled by secret knowledge. Further into my Hip Hop awareness I’d see more and more of the records that my parents owned. That was and is still a real special thing that cannot be replaced. My parents aren’t here anymore, and the knowledge that all I need do is put on a Dennis Brown or Ijahman record to help bring good thoughts of my mother is a real jewel. My father passed a longer time ago in the States, but a few James Brown songs fire the memory cards up nicely. I imagine how the both of them would react to me playing their music and smile.

Over the last few months I’ve become a lot more pro with my collections. Through the years, thousands of comics, mixtapes, soundtapes, books, films and records have been crammed into very small spaces for the sake of future entertainment. And to show my now full grown adult responsible self I decided to take the strain off of a few of these tiny black holes and buy decent containers for all these records.

Pretty much every record I own has meaningful history attached to it. I don’t own as many as sum but as they line up in boxes across the wall, I tend to think of a different future where tech didn’t get smaller with CDs and MP3s but a place where the USB keys are these 12 and 7 inch records. The times and the emotions etched into the records are so much bigger than can be contained and I still love allowing them to roam through the air every now and then.

They have earned the release because they have always been there for me.

This isn’t the place I was born or where I spent the most time but it is where formative years were grown. It means sumthing to live in a place, have to leave, and only have these reflections as reminders.

Even once I finally leave the bedroom I grew up in, these special memories will still be here, at home.

If you enjoyed Juice’s example and would like to tell your own Harkive story in a similar way, you can do so by emailing submit@harkive.org on or after 19th July with the tale of your listening day, writing as much or as little as you want. If email is not your thing, you can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

Harkive 2016 is just 1 day away. We do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. If Harkive sounds interesting, please do help us spread the word by telling your friends about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story. You can read our quick guide to the project here.

We’re now on the final countdown to Harkive 2016, with just 2 days to go. As we have done in previous years, in the run up to the big day we’ll be posting some ‘example’ stories from people who do interesting things with their music listening. Today we welcome James Cherry, Broadcast Manager for independent music publisher Sentric Music.

Based in Liverpool and with staff across Europe, Sentric provides artists with a variety of music business services connected to rights management, including royalty collection and synchronisation. Alongside his role of Broadcast Manager, James also focuses on content management, giving artists the help they need to establish themselves in an increasingly competitive market. You can find out more about Sentric Music on their website, or you can follow them on Twitter.

James kindly agreed to keep a record of his music listening for Harkive, and here is his story.

7.16 – I’m up and out to the gym early, my Discover Weekly playlist on Spotify refreshed so I throw that on. It usually provides a few gems, and this week is no different. Zibra’s ‘Flat in Dagenham’ and Gordi’s ‘So Here We Are’ are the standouts.

7.41 – I arrive at the gym, removing my headphones Jess Glynne’s ‘Don’t Be So Hard On Yourself’ is playing over their internal radio as I head to the changing room.

7.47 – Heading into the actual gym I put my gym playlist on through Spotify. It’s one of my oldest playlists that I’ve curated over five years, a solid blend of high tempo pop, heavier indie rock mixed with traces of hip-hop. Duke Dumont’s latest ‘Ocean Drive’ transitions to Talib Kweli’s ‘Get By’ to Spring King’s ‘City’. It might not be for everyone, but it works for me.

8.50 – Discover Weekly is back on for the 20-minute walk to the office, not too much to report here I skip quite a few of the tracks. I’m not overly impressed with this second listening session , so I eventually turn it off and remove my headphones.

9.10 – Stop off at the local spar to pick up some milk for the office. Justin Timberlake’s ‘Can’t Stop This Feeling’ is on the radio, that’s a track I’ve heard played to death over the last month so I let out a sigh.

9:46 – We’ve made it to work, and as I’m out for the afternoon I’m keen to crack on with my backlog of emails. It’s headphones on and hit play on Spotify’s ‘Music For Concentration’ playlist. As I get older I’m finding myself listening to more and more music designed for focus.

10:42 – Emails completed we are headphones down and back in the room. What I find out to be Spotify’s One Week One playlist is on the Office Sonos. Can’t say I take much interest but Kant’s ‘Close to the Wire’ and Bob Marley & the Wailers ‘Is This Love – Remix’ perk my ears.

13:48 – It’s our regular A+R meeting at Sentric where we run through all of the latest exciting artists and bands that have joined recently. We have over a hundred to run through, so there is no messing about. We skip between Spotify, Soundcloud and iTunes to listen to the latest offerings. Standouts came from Litany, Old Sea Brigade, Mullally and Benedict Benjamin.

16:38 – Back in the office for the final part of the day and Nancy Sinatra’s album ‘Nancy & Lee’ is on the Sonos. I only catch the final track ‘I’ve Been Down So Long’.

17:05 – The office is starting to thin out so I put my ‘2016’ Spotify playlist on the Sonos. I’ve created a yearly playlist since 2010, it’s a great way to track the evolution of my music taste, and pinpoint the key tracks in my life’s soundtrack. A track qualifies for the playlist if I listen to it over three times and still like it. Basic I know, but it works for me.

17:11 – Still in the office, I notice a former Sentric band The Hunna are playing a Facebook live stream for Billboard in New York so I pop my headphones on to catch ‘Bonfire’.

17:36 – Still in the office, I realise I’ve been listening to silence with my headphones on, so I take them off and catch Chairlift’s ‘Polymorphing’ and Kano’s ‘This Is England’ off my 2016 playlist before calling it a day.

19.57 – Back home, I stick the telly on to catch the Italian football team singing their national anthem.

20.34 – While watching the football my girlfriend, Louise walks in from the kitchen and proceeds to serenade me with Craig David’s Live Lounge cover of Justin Bieber’s ‘Love Yourself’.

If you enjoyed James’ example and would like to tell your own Harkive story in a similar way, you can do so by emailing submit@harkive.org on or after 19th July with the tale of your listening day, writing as much or as little as you want. If email is not your thing, you can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

Harkive 2016 is just 2 days away. We do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. If Harkive sounds interesting, please do help us spread the word by telling your friends about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

Thanks again to James for his story. If you’d like to follow his activities, you’ll find him as @JamesHCherry on Twitter. We’ll have another story for you tomorrow as the Harkive 2016 countdown continues.

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story.

We’re now on the final countdown to Harkive 2016, with just 3 days to go. As we have done in previous years, in the run up to the big day we’ll be posting some ‘example’ stories from people who do interesting things with their music listening. Today we welcome Vanessa Lobon and Colm Forde, the good people behind Doc’n Roll Films.

Doc’n Roll Films was set up in 2013 to build a nation-wide platform for the distribution and exhibition of alternative music documentaries. Focused primarily on first and second time filmmakers, Vanessa and Colm provide support and guidance through the industry’s maze. Based in London, with an annual autumn festival of premiere films across the city’s independent cinemas, they are gradually branching out to the regional cities with weekend editions in Brighton, Manchester and Liverpool.

After meeting with Harkive at Liverpool Sound City earlier this year, Vanessa and Colm kindly agreed to keep a record of their music listening day. Here is their story.

A regular day for the core Doc’n Roll team – Colm Forde (Programmer) and Vanessa Lobon (Artistic Director)

Alarm goes off, it’s 8:15

Another hectic day ahead, as we’re entering the build up period to our annual festival in November.

First thing,…on with the radio – Shaun Keaveny’s 6 Music show.

He sounds little bit grumpy today but good tunes to start the day, Roisin Murphy’s “Ten Miles High”, The Smiths “What difference is it makes”, White Denim “Had 2 know”…

Breakfast, showers and we are ready for work,….from home today.

Sifting through and answering emails we’ve still got the radio on 6, with Lauren Laverne,….ESG’s Erase You a particular favourite,…‘til 12pm….when we start to listen to a great show off RTE Radio 1 player. The South Wind Blows, from Philip King of Other Voices festival, is a weekly Saturday evening show broadcast from Dingle, in Kerry,….well worth exploring!

His one-hour programme has a great selection of folk/rock tunes,.. Bob Dylan, The Waterboys, The Beatles, Lisa Hanigan. A cool mix of old and new bands. Where I was first exposed to The National, Laura Muluva, Villagers…

Colm is the cook, so while he is prepping he’s got 6 Music on the kitchen radio in the background.

I’ve decided to listen to one of our recently acquired albums as I’m still working in the office, Car Seat Headrest –Teens of Denial,… American indie rock. It’s a grower, been hearing a lot recently about these guys.

Once lunch is over, we’re both back to researching and sorting through social media leads on docs being released in 2017. One of these ‘in-production films’ profiles the early days of the UK Hip-Hop scene,….so for a change of mood, out comes my Gangster’s Chronicle: Best of London Posse album for some good witty early 90’s street poetry.

An email update on the progress of a great doc on the horizon called Northern Disco Lights: The Rise and Rise of Norwegian Dance Music, inspires a search through our vinyl for a taste of Röyksopp’s Melody AM album.

The latest draft of our festival poster design arrives, so we consult via Skype with our designer on what’s good, what needs tweaking…..

Another quick search through Mixcloud for a soundtrack to this task and where off with a classic Norwegian cosmic disco set, Prinz Thomas’ et al, ending 45 minutes later with an impromptu boogie as Todd Terje’s Inspector Norse hits….

Dinnertime,….radio is on again, prepping to 6 Music, Marc Riley’s selection is a ritual, as his live sessions and general banter shake the evening and mood up a little.

As evening tilts towards night, we pick a new music doc from our to-watch list. It’s almost a nightly occurrence these days, as we’re currently swamped with a backlog of 11 films waiting in-line.

This is a great opportunity for us to discover new bands, broaden our knowledge and learn about some music genres that we are not overly familiar with, like jazz or metal. This exposure to new sounds often leads us to new album discoveries via Youtube, Soundcloud, Spotify….etc.

We end the day listening a few albums on our record player.

A good selection of down-tempo tunes from Bill Wither’s Greatest Hits, The Shins’ Wincing the Night Away,,..closing with Yo La Tengo’s And Then Nothing Turned Itself Inside (over and) Out….

If you enjoyed Vanessa and Colm’s example and would like to tell your own Harkive story in a similar way, you can do so by emailing submit@harkive.org on or after 19th July with the tale of your listening day, writing as much or as little as you want. If email is not your thing, you can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

Harkive 2016 is just 3 days away. We do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. If Harkive sounds interesting, please do help us spread the word by telling your friends about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

Thanks again to Vanessa and Colm for their story. If you’d like to follow their activities, you’ll find them as @docnrollfest on Twitter. We’ll have another story for you tomorrow as the Harkive 2016 countdown continues.

Harkive is an annual online popular music research project that invites people to tell the tale of How, Where and Why they listen to music on a single day each year. The aim of the project is to capture for posterity a snapshot of the way in which we interact with the sounds and technology of today.

On Tuesday 19th July Harkive is returning for its fourth year. We hope you’ll join us by telling Harkive the story of your music listening day.

In this quick guide, you’ll find everything you need to know about joining other music fans around the world on 19th July. We’d like you to help us add to the 8,000 stories gathered by the project since we launched in 2013.

Why tell your story?

Millions and millions of people will be listening to music on 19th July, but no two people will listen in precisely the same way, or for the same reasons. That makes you interesting.

You might use certain products, services, formats and technologies that are common to many others. You might spend the day listening to the same radio station as millions of others. Or you might listen to one song via headphones. You might go to a gig, or hear music in a restaurant. Whatever your experience, your motivations and the situations you find yourselves in as you listen, will be unique. It is the unique nature of your story that we are trying to capture.

How, Where and Why you listen to music is fascinating: We’d like you to tell us all about it.

How to tell your story

We’ve aimed to make the process of telling your story as easy as possible, and you can tell it in a variety of ways. Hopefully there is one that suits your habits already, and you won’t need to go too far out of your way to do it.

You can post to social media platforms, such as Twitter, Instagram and Tumblr, simply by adding the #harkive hashtag to your posts. Or you can ‘like’ the Harkive Facebook page and post something to our wall. You can post as many times as you like across the day.

If you’d like to take your time and write something a little longer, you can email your story to us, or post it via our online form.

A full list of the ways you can tell your story is available on the How To Contribute page.

Would you like to see some examples?

Every year, as Harkive approaches, we post some example stories from people involved with popular music. These have included stories from musicians, journalists, technologists, DJs, label owners, academics, and record collectors. Have a look back through the blog to see the example stories posted this year, or look at the examples page to see stories from 2013 onwards.

Another way of looking at past contributions to the project is through the Harkive Explorer, an interface that shows contributions from Twitter. You can search through this by looking for particular keywords (names of artists, places, and so on), or through selecting different formats and services.

Remember, though, that there is no right or wrong way to tell your story. You can write as much or as little as you want, and send as many entries as you like.

There are prizes…

As an extra incentive to join us on Tuesday 19th July, we have a small number of items donated by record labels and other organisations to give away. These include CDs, t-shirts and vinyl records. Once Harkive 2016 is over, we’ll draw names at random from a hat and winners will be announced here on the site.

…and live Data Visualisations

Throughout the day on Tuesday 19th July, you can see how things are shaping up by looking at our new Data Visualisation Dashboard. Here you’ll be able to see information about the stories as they start to arrive on Harkive day, including a story count, timeline, word cloud, and other insights, all powered by the Harkive API.

Can you tell us more?

For 2016 we also have a Music Listening Survey. This takes around 5-10 minutes to complete, and will provide the project with some additional context about your music listening that will be crucial to the research that underpins this project (more on that below). Whether or not you intend to join in with Harkive 2016, please do take a moment to complete the survey.

By way of background, we road-tested the survey with a UK-based vinyl and CD manufacturer recently. Their staff completed the survey and produced this beautiful infographic. We’d love to include your responses in something similar.

What happens after Harkive 2016?

Harkive forms the basis of a PhD research project at Birmingham City University by Craig Hamilton. Shortly after Harkive 2016, the stories and other data collected by the project will be analysed and will inform the completion of Craig’s thesis. Information about any publications or conference papers that emerge from this research work will be posted to this site, and via the Harkive social media channels. Harkive will return in July 2017 for it’s 5th year.

What happens to my data?

This project has been approved by Birmingham City University’s Research Ethics Committee, and for more information on that please see our Research Ethics statement. None of the personal information (email addresses, etc) provided by you to the project will be made available to 3rd parties without your consent. Elements of the data will be made available via the Harkive API research tool. Please feel free to contact us if you have any questions related to this.

Please help us spread the word

We’d love to hear from as many people as possible on Tuesday 19th July, so if you think the project is interesting, please do tell your friends about Harkive and encourage them to join in. You can share this post with the following link: http://www.harkive.org/h16

Ask us anything

If you have any questions about Harkive, or would like some guidance about how to tell your story, please feel free to email us, or say ask us on Twitter, where we are @harkive

We’d love to hear your story on Tuesday 19th July. Please do join us by telling Harkive your story.

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story.

We’re now on the final countdown to Harkive 2016, with just 4 days to go. For the past few days we’ve been posting example stories from interesting people involved with popular music – check back through the blog to see these – but for today we’ve got something slightly different for you, from the good people at Key Production.

Key Production is a well-established music & media manufacturer. They have been manufacturing CDs, DVDs, vinyl and print for over 25 years, specialising in bespoke packaging and project management for the music industry. If you’ve bought records, CDs or DVDs by UK artists at some point over the last decade or so, there’s a fair chance it was made by Key Production.

Harkive originally approached Key in order to see if someone at the company would be interested in writing a Harkive story for the blog, much like the ones you’ve been reading here this week. Key thought it would be interesting, however, to see how the company’s employees as a whole enjoy music in and outside of the workplace.

This development was good news for us, as for 2016 we have an additional element to our research process. Alongside gathering stories on Tuesday 19th July, we have also devised a Music Listening Survey. The data gathered by this survey is intended to augment the stories gathered on 19th July and provide additional context for the analysis stages. The survey is now live at http://www.harkive.org/h16-survey and takes around 5-10 minutes to complete. Whether or not you intend to take part in Harkive 2016, we hope that you will take the survey, and also hope, of course, that you will enjoy completing it.

Working with Key has allowed us to road-test the survey. They took elements of it – specifically the sections on General Music Listening, Technology & Formats, and Recommendation & Discovery – and circulated it amongst their staff, which has led to the following infographic that provides a fascinating insight into the listening habits and practices of a group of people who work with music on a daily basis.

By completing the Harkive 2016 Music Listening Survey, we hope you will help us to produce similarly interesting insights into the practices and opinions of the those contributing their stories to Harkive.

There are just 4 days to go until Harkive 2016, and we do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. You can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

If Harkive sounds like something your friends may be interested in, please do help us spread the word by telling them about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

Thank you to all at Key Production for working with us on this element of our research. You can follow their activities on Twitter, where they are @keyproduction, or visit their website to find out how they can help with your physical product needs.

We’ll have another story tomorrow as the countdown to Harkive 2016 continues.

29 people within Key Production completed the survey anonymously via Survey Monkey. The data was then analysed with the aid of Survey Monkey reports and Microsoft Excel, then translated into graphs enriched with artworks in order to create the infographic above. Not all the 42 questions were included in the analysis. Upon request, will be happy to provide you with the full questionnaire and statistics.

Moreover, with recorded media being our focus, we can now gladly back up with data that our staff not only works to deliver to clients the best products, but also has a real passion for the physical format. We definitely love what we do!

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story.

We’re now on the final countdown to Harkive 2016, with just 5 days to go. As we have done in previous years, in the run up to the big day we’ll be posting some ‘example’ stories from people who do interesting things with their music listening. Today we welcome musician William Doyle.

After releasing two acclaimed albums as East India Youth, William is now heading up your wilderness revisited,a multimedia art project that looks at how we interact and engage with British post-war suburban environments, specifically new places built in the last 30 years, while also considering the challenge of their designs for the future. The project focuses on the questions and concerns of human individuality within the suburban built environment, and how the development of these places affects the harmony – both socially and ecologically – that is sought within them. The work of your wilderness revisited will eventually be compiled into an audio/visual exhibition that will include photography, video art and music working together to create a unique look at our surroundings, and to inspire discussion to help people better engage with their own.

William kindly agreed to keep a record of his music listening one day earlier this month, and here is his story.

I start every morning by doing around 20 to 30 minutes meditation, and then will often sit afterwards and listen to one or two songs on headphones and just focus on them, letting them help the day begin. This morning I listen to ‘Blackpool Late Eighties’ by James Holden, from his album The Inheritors, an album which only seems to improve upon each listen. It’s really one of the greatest released in the last decade, and I find the spaciousness and depth of the production on it to be transportive and inspiring.

I then head downstairs and do the washing up. This is a routine I’m enjoying at the moment since the washing up is fairly low concentration job and so I can really hone in what I’m listening to. Today I opt for the radio. I’ve been a big BBC 6 Music listener for the last 8 or 9 years now, although my frequency of listening habit will fluctuate. Starting the day listening to Shaun Keaveny’s breakfast show is almost guaranteed to make me laugh or smile and you can’t really ignore the positive effect this has on the rest of your day.

This morning’s highlights over an hour of listening are ‘Customer Service’ by Jurassic 5 (which I’ve heard twice recently so I’m guessing it’s new?), ‘Silvering’ by Lonelady, ‘Here Comes The Breeze’ by Gomez (which I don’t really enjoy, but I do when impersonating the singer with the higher-pitched bluesy voice), the new Róisín Murphy tune ‘Ten Miles High’, and ‘Life Itself’ by Glass Animals (which has some really strange lyrics.) The last tune I leave on is Beyond The Wizard’s Sleeve’s ‘Black Crow’ featuring the wonderful Holly Miranda on vocals. It reminds me that I need to listen to the BTWS album as everything I’ve heard so far has been brilliant, and so I decide to set aside time later to dive in. My good friend Hannah Peel contributed vocals over this album and ‘Diagram Girl’ is one of my favourite songs in the last year.

Next I finish watching ‘I Often Dream of Trains In New York’ which is a live recording of Robyn Hitchcock playing his classic album ‘I Often Dream of Trains’ accompanied by guitarist Tim Keegan and multi-instrumentalist Terry Edwards, who seems to be cropping up a lot in my musical thoughts lately (I’m a big fan Terry, if you’re reading!). The reason I’m watching this is for research as I want to do a piece of writing on this album. It’s been hugely influential to me over the years and it has been even more so recently. I think it’s a generally overlooked wonder. The film is great as well, with interview snippets in between some songs that shed some insight into the history of the album.

The most music I listen to after this point is all of my own. I’m working on a lot of music at the moment and try to dedicate 7 or 8 hours daily to this. This doesn’t sound like much time but with some focus over 2 hour increments, you wind up getting a lot done without becoming tired and frustrated. Tiredness and frustration lead me to tinkering and making useless changes, listening to the same part over and over again, so a concentrated period is better than an endlessly sprawling one.

Today the results of the Chilcot Inquiry into the Iraq war are published. I listen to ‘Harrowdown Hill’ by Thom Yorke. Chills. Through the filter of everything that’s been going on, the song’s tone of an acknowledged darkness feels strong even outside of the context of the lyrics. This feeling catches me off-guard for a moment. https://en.wikipedia.org/wiki/Harrowdown_Hill

I listen to Beyond The Wizard Sleeve’s album The Soft Bounce in the bath. Slightly misjudged the setting for it, but the sound of it is incredible. Going to give it some more goes tomorrow, but I think they’ve made a winner.

Today, after recalling some kind of industrial dub atmosphere lodged deep in my memory and after a bit of searching, I remember that producer Adrian Sherwood had something to do with a track that had an effect on me at some point. I’d only heard it once but remember it vividly for some reason. This is quite a common occurrence for me, however I rarely note things down at the time as I prefer them to be held in that moment as much as possible, and if they return to me later then it’s a fun experiment to try to uncover it. It takes me a while to search through Sherwood’s massive discography but the track turns out to be ‘Fade Away’ by New Age Steppers, which was the first single released on his On-U Sound label. I then spend 45 minutes listening to the self titled album that it features on and I’m pleased to have uncovered this right now. I think I’ve been unconsciously adding dub-like effects to drum machine parts in some new songs I’m working on, so it’s nice to hear some sonic ideas in this context that I could perhaps go further on.

Finish the day, as I often do, with a play on Brian Eno and Peter Chilver’s Trope app. Final thought: We need more generative music.

If you enjoyed William’s example and would like to tell your own Harkive story in a similar way, you can do so by emailing submit@harkive.org on or after 19th July with the tale of your listening day, writing as much or as little as you want. If email is not your thing, you can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

Harkive 2016 is just 5 days away. We do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. If Harkive sounds interesting, please do help us spread the word by telling your friends about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

Thanks again to William for his story. If you’d like to follow his activities, you’ll find him as @your_wilderness on Twitter. We’ll have another story for you tomorrow as the Harkive 2016 countdown continues.

On Tuesday 19th July Harkive will return for its fourth year to once again collect stories online from people about the detail of their music listening experience.

The project asks people to tell the tale of How, Where and Why they listen to music on a single day each year, with the aim of capturing for posterity a snapshot of the way in which we interact with the sounds and technology of today. Since launching in 2013 the project has gathered over 8,000 stories, and on Tuesday 19th July we’ll be doing it all again. We hope you’ll join us by telling Harkive your story.

We’re now on the final countdown to Harkive 2016, with just 6 days to go. As we have done in previous years, in the run up to the big day we’ll be posting some ‘example’ stories from people who do interesting things with their music listening. Today we welcome Claire Gevaux, Creative Director of Help Musicians UK.

Help Musicians UK is the leading UK charity for professional musicians of all genres, from starting out through to retirement. They help at times of crisis, but also at times of opportunity, giving people the extra support they need at a crucial stage that could make or break their career. You can find out more about their work by visiting their website, or following them on Twitter.

Claire kindly agreed to keep a record of her music listening on Thursday 7th July for Harkive, and here is her story.

7.38

Waking up in a hotel room in Liverpool, the morning after the night before, and the strangely appealing Paranoid Android from the Radiodread album by Easy Star All Stars is still floating around my head. There aren’t any clever devices for playing music in the room, so I resort to Radio 6 Music on the TV – I wonder if Shaun Keaveny would like my earworm this morning. First Aid Kit starts my day with a silver lining and a decaf coffee.

9.57

Leaving the Albert dock, I walk across Liverpool listening to Mendelsohn’s Midsummer Night’s Dream as I had the privilege of sitting in on a rehearsal with the Hallé Orchestra and I was fascinated to hear and watch Sir Mark Elder’s precise direction of the whispering passage in the first movement. It also brings to mind the recent celebration of Shakespeare’s death and the relationship between music and other artforms and in telling the stories of our lives.

11.01

By late morning, I arrive at my destination, Milpafest, Britain’s leading Indian Art Development Trust, based at Liverpool Hope University. Alok Nayak, Artistic Director, tells me about his organisation which educates, promotes and trains people of all ages in Indian arts. Although based in Liverpool, it is national in its reach and international in its outlook, and can take credit for creating its own sub-genre influenced by film and other artforms as well as contemporary life in Britain. We talk about the challenges for artists to achieve long term, sustainable careers in Indian Music, with few making it as international soloists but that there are routes to performance and orchestral careers thanks to the work he has championed. On leaving, Alok gives me a CD of Tarang, the UK’s Indian classical music ensemble to listen to when I get home.

12.04

My next destination is the regenerated Baltic Triangle area of Liverpool, where the Community Interest Company landlords are ensuring a thriving creative industries hub whose tenants benefit from lower rents and opportunities to collaborate which are fundamental to their success. As I walk past posters advertising the next Biennale and public art celebrating the city’s heritage, I’m reminded of the incredible journey Liverpool has been through, particularly in recent years. Not only of heartbreak and tragedy but also how the people of Liverpool embraced the importance of the arts and, in particular, music which gave them pride in themselves and their city. I am reminded of the commission that Royal Liverpool Philharmonic Orchestra undertook to commemorate the 96 victims of the Hillsborough Stadium disaster. Working with composer, Michael Nyman, Symphony No.11: Hillsborough Memorial includes the names of all those who died in 1989 and was performed in Liverpool Cathedral in 2014 as part of the Biennale.

12.43

My first meeting in the Baltic Creative Campus is with Liverpool Sound City, and Becky tells me about their plans to enhance the network of festivals in the North West and to tackle the lack of appropriate industry support for emerging and diverse talent who can develop into the status of festival headliners.

13.42

Over a quick lunch in Unit 21 (which reminds me of the similar spaces that popped up all over Hackney in the past 8 years) I listen to my playlist of artists we’ve been able to support through organisations such as Merseyside Arts Foundation. She Drew the Gun has been working hard since they were given support from Merseyside Arts Foundation for much needed studio time and mentoring. Since then, the ‘dreamy lyrical psych-pop band’ has gone on to win Glastonbury’s Emerging Talent Contest. Check out ‘If You Could See’. Another great Merseyside achievement has been The Lottery Winners, who were successful through our Emerging Artist Fund with PledgeMusic and who we showcased at The Great Escape. After my meeting with Peter Shilton, I listen to their debut EP with indie pop greats like Elizabeth and Young Love I can’t wait to hear their first album, now possible with the recent signing to major label Warner Bros.

15.23

Leaving the creative industries quarter, I switch my playlist and listen to the new release from Perhaps Contraption playing at the Manchester Jazz Festival at the end of July. As a group they are certainly pushing boundaries and creating a unique musical experience. Check out their second album, Mud Belief but also watch them live as they’re great performers too.

I’m meeting with Yaw next, Creative Director of ‘Nothin but the Music’ an academy for young talent in Liverpool to be empowered to have successful careers in the music industry. Yaw brought some of his recent graduates to a showcase in Camden where I met the incredibly talented Jalen Ngonda. After our meeting, I listen to Jalen’s ‘You Deserve What You Got’ on my final walk across the city to Hope Street and the Liverpool Philharmonic Hall.

19.23

My day ends with a wonderful concert celebrating 10 years of conductor Vaisly Petrenko’s tenure at Royal Liverpool Philharmonic Orchestra. An evening of Elgar’s interpretation of the Italian Riviera ‘In the South (Alassio)’, Shostakovich’s very modern Cello Concerto No1 in E flat and ending on Rachmaninov’s Symphony No.3 in A minor which, although didn’t have many contemporary admirers, is a wonderful homage to Russia, its history and his devotion to his homeland.

22.14

On my wander back to the Albert Dock, I’m back in contemporary mode, and reflecting on my love of northern cities and their relationship to the people who live there. Liverpool particularly reminds me of home, of Newcastle, where I grew up and discovered punk, goth and was influenced by my mum’s love of Stan Getz and Motown. Musing on the thoughts of home, I listen to Samantha Whates ‘Granny’s House’ in which she explores what makes us think of home and, for her, in this song at least, it’s a cup of tea. We helped Sam when she was injured on tour and we were able to, literally, get her on her feet again. She generously support Help Musicians UK in our recent Musicians Against Depression #MAD campaign (musicanddepression.org.uk) and talked openly of her own experiences with mental health as a professional performer.

As I walk around the docks, it occurs to me that I should end my stay I Liverpool with another childhood influence, this time from my sister. We spent many happy hours listening and playing Beatles songs so my final choice of the day is the album, Revolver. With its ambitious diversification sparking new musical subgenres, its eclectic nature feels an appropriate place to conclude my own diverse musical journey of the North West.

If you enjoyed Claire’s example and would like to tell your own Harkive story in a similar way, you can do so by emailing submit@harkive.org on or after 19th July with the tale of your listening day, writing as much or as little as you want. If email is not your thing, you can contribute your story in a number of other ways, such as by Tweeting with the hashtag #harkive across the day, by posting to the Harkive page on Facebook, or by adding stories and images to Tumbr and Instagram – just remember to add the hashtag #harkive to each of your posts. More information on the ways in which you can tell your story are on the How To Contribute page.

Harkive 2016 is just 6 days away. We do hope you’ll join us on Tuesday 19th July by telling us the story of your listening day. If Harkive sounds interesting, please do help us spread the word by telling your friends about the project. In the meantime you can keep an eye on the project by following us on Twitter, or by liking our Facebook page. If you have any questions about the project please feel free to email us.

Thanks again to Claire for her story. If you’d like to follow her activities, you’ll find her as @ClaireGevaux on Twitter. We’ll have another story for you tomorrow as the Harkive 2016 countdown continues.